use int32 to init global_step explicitly

tensorpack/tfutils/common.py

@@ -46,7 +46,7 @@ def get_global_step_var():
         assert scope.name == '', \
                 "Creating global_step_var under a variable scope would cause problems!"
         var = tf.get_variable(GLOBAL_STEP_OP_NAME, shape=[],
-                initializer=tf.constant_initializer(),
+                initializer=tf.constant_initializer(value=0, dtype=tf.int32),
                 trainable=False, dtype=tf.int32)
         return var
 

tensorpack/tfutils/symbolic_functions.py

@@ -72,9 +72,9 @@ def class_balanced_sigmoid_binary_class_cross_entropy(pred, label, name='cross_e
     #eps = 1e-12
     logstable = tf.log(1 + tf.exp(-tf.abs(z)))
     loss_pos = -beta * tf.reduce_mean(-y *
-            (logstable - tf.minimum(0, z)))
+            (logstable - tf.minimum(0.0, z)))
     loss_neg = (1. - beta) * tf.reduce_mean((y - 1.) *
-            (logstable + tf.maximum(z, 0)))
+            (logstable + tf.maximum(z, 0.0)))
     cost = tf.sub(loss_pos, loss_neg, name=name)
     return cost